Stochastic composite simulation models can be used to estimate performance measures for complex stochastic systems of systems. Composite simulation models are made up of loosely coupled component models that communicate by reading and writing datasets. Output data from upstream “source” component models are transformed as needed to a form suitable for input to downstream “target” component models. Such loose coupling and data transformation facilitates cross-disciplinary collaborative modeling and simulation as well as re-use of existing simulation models. Further, composition via loose coupling facilitates dealing with experts in different domains, as it avoids the need for massive re-coding or strict enforcement of a common platform, application programming interface (API), or communication protocol.